Related Experiment Video
Updated: Oct 9, 2026

Development of a Lateral Flow Immunochromatographic Strip for Rapid and Quantitative Detection of Small Molecule Compounds
Published on: November 13, 2021
Overcoming sensitivity limitations in lateral flow immunoassays for small-molecule detection: from tracer engineering
Xinyi Gao1,2, Xiaoyi Chen1,2, Mengxiang Su3,4
1Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing, 210009, China.
Abstract:
Typical small-molecule contaminants such as mycotoxins, drug impurities, food additives, and antibiotics can enter living organisms through multiple pathways, which may cause a range of health problems. Timely detection of abnormalities in these small molecules is crucial for maintaining health. The lateral flow immunoassay (LFIA), as a simple, rapid, and intuitive detection method, allows for real-time analysis of samples and has become an indispensable tool for on-site screening. However, the sensitivity and robustness of traditional gold nanoparticles (AuNPs)-based LFIA remain insufficient for reliable detection in complex matrices, largely due to limitations in signal generation and assay architecture. This review critically analyzes the recent development of LFIA for small-molecule detection from two perspectives. Firstly, we focus on advances in assay format engineering, including oriented antigen-antibody coupling, heterologous coating approaches, and innovative non-competitive configurations, which collectively improve recognition efficiency and analytical performance. In addition, signal amplification strategies through tracer engineering are discussed, including surface modification, multivalent labeling strategies, and colorimetric- or fluorescence-based signal enhancement. For complex detection matrices, the incorporation of magnetic nanoparticles (MNPs) and surface-enhanced Raman scattering (SERS) has also been explored as an effective way to strengthen signal output. Finally, this article points out the technical limitations and future development trends, aiming to provide conceptual guidance for the rational design of next-generation LFIA.

